基于HMM的机械设备运行状态评估与故障预测研究综述
发布时间：2018-09-08 19:48
【摘要】：随着对机电设备安全性和可靠性要求的不断提高,准确获取趋势性故障发展历程的退化特征信息并建立有效的故障预测模型是提高设备运行可靠性的关键。隐马尔可夫模型(Hidden Markov Model,HMM)具有描述隐藏状态和观测状态的双随机过程属性,与设备的退化过程在某种程度上是相似的,因此成为故障预测模型的研究热点。综述国内外基于隐马尔可夫模型的退化评估与预测方法,重点论述基于隐马尔可夫模型及其改进方法隐半马尔可夫模型(Hidden semi-Markov Model,HSMM)的机械设备故障预测方法,分析比较各种方法的优缺点,并总结展望基于隐马尔可夫模型故障预测方法的发展趋势。
[Abstract]:With the increasing requirements of safety and reliability of electromechanical equipment, it is the key to improve the reliability of equipment to obtain the degradation characteristic information of the trend fault development history and establish an effective fault prediction model. The Hidden Markov Model (Hidden Markov Model,HMM) has the properties of double stochastic processes to describe the hidden state and the observed state, which is similar to the degradation process of the equipment to some extent, so it has become the research hotspot of the fault prediction model. This paper summarizes the methods of degradation assessment and prediction based on hidden Markov model at home and abroad, and emphatically discusses the methods of mechanical equipment fault prediction based on hidden Markov model and its improved method, hidden semi-Markov model (Hidden semi-Markov Model,HSMM). The advantages and disadvantages of various methods are analyzed and the trend of fault prediction based on hidden Markov model is summarized.
【作者单位】： 南通大学机械工程学院;
【基金】：国家自然科学基金项目(51405246) 江苏省自然科学基金项目(BK20151271) 南通市应用基础研究-工业创新项目(No.GY12016010)资助~~
【分类号】：TH17
本文编号：2231514
[Abstract]:With the increasing requirements of safety and reliability of electromechanical equipment, it is the key to improve the reliability of equipment to obtain the degradation characteristic information of the trend fault development history and establish an effective fault prediction model. The Hidden Markov Model (Hidden Markov Model,HMM) has the properties of double stochastic processes to describe the hidden state and the observed state, which is similar to the degradation process of the equipment to some extent, so it has become the research hotspot of the fault prediction model. This paper summarizes the methods of degradation assessment and prediction based on hidden Markov model at home and abroad, and emphatically discusses the methods of mechanical equipment fault prediction based on hidden Markov model and its improved method, hidden semi-Markov model (Hidden semi-Markov Model,HSMM). The advantages and disadvantages of various methods are analyzed and the trend of fault prediction based on hidden Markov model is summarized.
【作者单位】： 南通大学机械工程学院;
【基金】：国家自然科学基金项目(51405246) 江苏省自然科学基金项目(BK20151271) 南通市应用基础研究-工业创新项目(No.GY12016010)资助~~
【分类号】：TH17
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